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Exploring Dell EMC Networking for vSan

This is the second entry in an insideHPC guide series that explores networking with Dell EMC ready nodes. Read on to learn more about Dell EMC networking for vSan.

Edge Computing Proves Critical for Drilling Rigs, Pipeline Integrity

This is the third entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to learn how edge computing is playing a role in operating drilling rigs, ensuring pipeline integrity and more. 

How Do I Network vSAN Ready Nodes?

Dell EMC vSAN Ready Nodes are built on Dell EMC PowerEdge servers that have been pre-configured, tested and certified to run VMware vSAN. This post outlines how to network vSan ready nodes. “As an integrated feature of the ESXi kernel, vSAN exploits the same clustering capabilities to deliver a comparable virtualization paradigm to storage that has been applied to server CPU and memory for many years.”

Energy Companies Embrace Deep Learning for Inspections, Exploration & More

This is the second entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to learn how energy companies are embracing deep learning for inspections, exploration and more. 

Case Study: Supercomputing Natural Gas Turbine Generators for Huge Boosts in Efficiency

Hyperion Research has published a new case study on how General Electric engineers were able to nearly double the efficiency of gas turbines with the help of supercomputing simulation. “With these advanced modeling and simulation capabilities, GE was able to replicate previously observed combustion instabilities. Following that validation, GE Power engineers then used the tools to design improvements in the latest generation of heavy-duty gas turbine generators to be delivered to utilities in 2017. These turbine generators, when combined with a steam cycle, provided the ability to convert an amazing 64% of the energy value of the fuel into electricity, far superior to the traditional 33% to 44%.”

Opportunities Abound: HPC and Machine Learning for Energy Exploration

The is the first entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to find out how machine learning is driving energy exploration. “Any tool that reduces the time needed to understand where the deposits are located can save a company millions of dollars.”

Squeezing Light could be key to Quantum Computing

“Scientists at Hokkaido University and Kyoto University have developed a theoretical approach to quantum computing that is 10 billion times more tolerant to errors than current theoretical models. Their method brings us closer to developing quantum computers that use the diverse properties of subatomic particles to transmit, process and store extremely large amounts of complex information.”

How Deep Learning Tech Can Contribute to Success

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the fourth article in a five-part series that covers the steps to take before launching a machine learning startup. This post covers how deep learning is contributing to success across a variety of industries.

DDN and Parabricks Accelerate Genome Analysis

Today DDN announced a Parabricks technology solution that provides massive acceleration for analysis of human genomes. The breakthrough platform combines GPU supercomputing performance with DDN’s Parallel Flash Data Platforms for fastest time to results, and enables unprecedented capabilities for high-throughput genomics analysis pipelines. The joint solution also ensures full saturation of GPUs for maximum efficiency and provides analysis capabilities that previously required thousands of CPUs to engage.

What Next? Entering the World of Machine Learning

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the final article in a five-part series that covers the steps to take before launching a machine learning startup. This article provides a variety of resources to employ when first exploring machine learning.